| 1 | Management Algorithm for Prevention of Mother-to-child Transmission of Hepatitis B Virus(2022)显示文摘The World Health Organization(WHO)has set the goal of eliminating hepatitis as a threat to public health by 2030.Blocking mother-to-child transmission(MTCT)of hepatitis B virus(HBV)is not only the key to eliminating viral hepatitis,but also a hot issue in the field of hepatitis B prevention and treatment.To standardize the clinical management of preventing MTCT of HBV and achieve zero HBV infection among infants,the Chinese Foundation for Hepatitis Prevention and Control organized experts to compile a management algorithm for prevention of MTCT of HBV based on the latest research progress and guidelines,including 10 steps of pregnancy management and postpartum follow-up,among which screening,antiviral treatment,and infant immunization are its core components. | Zhihua Liu Zhongdan Chen Fuqiang Cui Yang Ding Yunfei Gao Guorong Han Jidong Jia Jie Li Zengde Li Yingxia Liu Qing Mao Ailing Wang Wei Wang Lai Wei Jianhong Xia Qing Xie Xizhong Yang Xueru Yin Hua Zhang Liaoyun Zhang Wenhong Zhang Hui Zhuang Xiaoguang Dou Jinlin Hou | 2022 | Journal of Clinical and Translational Hepatology2022，10，5： | 2 |
| 2 | Myocardial Infarction Detection and Localization with Electrocardiogram Based on Convolutional Neural Network显示文摘Electrocardiogram(ECG)is widely used in Myocardial infarction(MI)diagnosis.The automatic diagnosis of MI based on the 12-lead ECG needs to consider not only the waveform change features in multi-resolution time series,but also the spatial correlation information between the leads.To this end,this work proposed multiscale spatiotemporal feature extraction method based on Convolutional neural network(CNN)for MI automatic diagnosis.First,the 12-lead ECG is first transformed into an ECG image through wavelet decomposition and 3-dimensional space reconstruction.The MI-CNN model is then constructed to identify MI using 41368 ECG images.Finally,we develop the LL-CNN model,which is utilized only after the ECG signal is identified as an MI event by the MI-CNN model,to localize MI by employing transfer learning to overcome the limited data problem.The proposed method has achieved an accuracy of 99.51%on MI detection,and a macro-F1 of 99.14%on MI localization.Moreover,the features visualization shows that U-wave has significant diagnostic value for MI.The proposed method significantly improves the performance of MI detection and localization compared with other methods.It is promising to be used for MI monitoring and diagnosis. | LIU Jikui WANG Ruxin WEN Bo LIU Zengding MIAO Fen LI Ye | 2021 | Chinese Journal of Electronics2021，30，5： | 0 |
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